CCC Intelligent Solutions Holdings Inc. (CCC) Earnings Call Transcript & Summary

Awesome. Thank you, everybody, for joining today, day 1. Pleasure to have the CCC management team here, CEO, Githesh Ramamurthy; and CFO, Brian Herb. I'm Dylan Becker, the research analyst that covers CCC here at William Blair. For all the necessary disclosures, you can find those at williamblair.com. Gentlemen, thank you for joining us today. Bill has slides that he'll be flipping through as well just as a reference point for context of what we're speaking about today.

But maybe as a way to kick it off, Githesh. For those that aren't as familiar with CCC here in the room today, can you give us a quick context kind of what CCC does, the value proposition you bring to the auto insurance ecosystem? And we'll dig into kind of the network dynamics and the benefits of that.

Super. So first I have to ask me, how many people have a car? How many people have insurance? Okay, same number of hands. So that tells me that on balance, $350 billion are collected in premiums and $300-plus billion are spent in auto claims. So what CCC does in a nutshell is to make that whole process efficient. So we have 35,000 customers. From insurance companies, collision repairs, part providers, car companies, it takes an orchestra to have a seemless process and duet. So that's really what we hope, deliver those efficiencies to those customers and, at the end, allows those customers to serve their policy owners, which clearly most people in this room are.

Maybe, Brian, piggybacking off of that, too. We've got close to 40,000 ecosystem players here. What does that equate to from a financial perspective? Obviously, a lot of scale in the business, but thinking about kind of the revenue profile, the financial profile, maybe some metrics to kind of peg that as well.

Yes, absolutely. So we are a Rule of 50 company. So if you look at past the last 5 years, we've averaged revenue growth on an organic basis of 11%. Last year, we finished with margins over 40%. We go back 5 years, the margins were 30%. So we've seen 1,000 basis points over a 5-year period as well. So we've been scaling the top line. At the same time, we have been scaling EBITDA as well. We operate in a large underpenetrated market. So we think about the TAM at about $10 billion. And now our revenues are coming up to about $1 billion. So we're just under 10% penetrated in our TAM. When you look at our current solutions that we have in the market or will be in the market this year, we look about half of TAMs covered on existing solutions, so about $5 billion, if we sold our existing solutions into the market. A couple of other metrics to hit on. We very much are a cross-sell story, upsell. NDR is 108, that's where we ended NDR last year. We have long relationships with our clients, and we -- they have varied the network, and softwares are sticky. We have a gross dollar retention of 99% as well. So those are some of the key metrics as we look at across the business.

And obviously, that's a very unique profile in and of itself. Githesh, you touched on this ecosystem kind of coming out. Obviously, working with the insurance carriers, working with the prepared facilities, working with the part providers, there's a lot of complexity in this ecosystem. Can you help us kind of get a sense of what's driving change across that ecosystem that have the complexity figures of it?

Sure. So if you look at the average car, complexity has increased pretty dramatically. Cars have more sensors, more parts, more computer chips, cameras and the whole length. So what that has done is increase -- a dramatic increase in the complexity of what it takes to evaluate how should I process this point. Should I repair this car? Should I total this car? What part should be purchased? And which repair facility can actually repair this car? It's a little different. So it creates a massive amount of complexity. And there's massive model proliferation. And by then, you add electric, you have hybrids, powertrains, a lot more complexity. At the same time, the industry is facing a very secular challenge. Shortage of labor. Quick show of hands, how many of you have friends who got into the collusion repair industry? Okay. So the influx of going into collusion repair is also less. So at the same time, people with 20 to 30 years of experience are retiring. So what we've been able to do is to really help our customers across the board manage these three things colliding incident: a substantial increase; inflation of cost; and increase in the cost of [ communicating ] the cost of insurance, primarily driven by the cost of claims; complexity of the vehicles; and the labor that is getting tighter and tighter across the industry. So technology is seeing -- technology is seeing this increasingly as a way to solve this.

And that probably drives benefits throughout the data that we've talked about as well, right? How do you think about the scale of the data that you guys are ingesting, what you guys can cover to address this complexity and what that means for delivering value, automation capabilities and things like the insurance that you do?

Yes. So the other thing we benefit from is that having wonderful customers across the entire ecosystem means we have about $1 trillion of historical data. That means data about parts, about parts procurement, about labor, about every medical claims, about these things. So that also feeds -- for about a decade, we've been investing in artificial intelligence for about a decade. We released our first commercial products in 2021. So the -- so that data set is increasingly helping deliver artificial intelligence, which is based on the datasets that we have. So that's been of enormous value, in addition throughout the customers' benchmark performance.

With that as well, too, that would obviously, in turn, I would think, drive a lot of competitive differentiation. How do you think about the competitive landscape off of that? Is this data something that really you guys have only been able to build out or there are other competitors out there that are using something similar?

There are really two dimensions, right, on the data. The first dimension is that given the breadth of the customer base we have, we operate the largest network in the industry by far of insured -- network of insurers, payers, parts providers, [indiscernible]. So by nature, it is the largest network with the most amount of transactions, and it generates a maximum value of each purchase point. We're an insurance company. We want to be able to network that gives you the broadest number of suppliers that are nearer. You want to have the broadest number of insurers. So that has been extraordinarily valuable in terms of the dataset. The second element of the network is the latency of the data. So that means, on a given day, the amount of data that we see, the amount of information flows that we see is substantial. So when we look at artificial intelligence, we look at drift in AI and the ability to correct and provide accuracy, that latency. So parts prices change in Tifton, Georgia or Nashua, New Hampshire, you can reflect those capabilities and statistically the valid sort of way very quickly. So scale, granularity and latency are all very important factors.

Yes. It's almost at hyperlevel precision that you guys can provide.

I think so.

Brian, you touched on some of the financial metrics with the emphasis on cross-sell. Maybe pairing with the data network, how we should think about kind of the core solution set that has been built out over time with more some of the emerging solutions, maybe the contribution, the size and scale?

Yes, absolutely. So if you look at the last quarter that we delivered the 11% top line growth, if you break it down, we had 3 points that came from new logos. We had 8 points that came from cross-sell/upsell. Within the 8, 7 -- about 1 point was in emerging new solutions. So new solutions are just starting to contribute and just starting to scale. The way we frame new solutions, they will be diagnostics, our subrogation solution, estimate STP are the three flagship. Then there's other releases that have just recently come into market, and there'll be more releases that come into market this year. We do expect the emerging solution set continuing to scale, and we've highlighted that. Today, it's 1 point of growth and contribution. That will continue to have a larger contribution, if you go to the second half of the year. This year, we think about more like 2 points at the end of the year. Over time, it's going to look more like 50-50 cross-sell/upsell coming from the emerging solutions versus solutions that we've established and had in market for years.

And Githesh, maybe give us a sense of what's some of those new emerging opportunities or initiatives are? And how that's been enabled by the ecosystem and data scale that you've built out?

Yes. You can see on the slide, there's a number of new emerging solutions. We've actually increased the amount of R&D and the number of solutions. Now -- and Estimate-STP is a great example of that. We released a product where once you have that, I don't know how many people in this room have had an auto claim, but we always have somebody come out to see your car. Today, carriers sends a link with CCC. You can actually go around your car, go click, click, click. AI will guide you through the taking of the photo. Literally, in seconds, it will tell you that, hey, this car can be repaired for exactly this amount, detailed estimate. And we have the largest network of repair facilities you can actually drop an appointment [indiscernible]. So you will search on Google. Even on Google Search, if you block an appointment in the calendar from CCC. So all of those capabilities, Estimate-STP is now -- we've gone from about 1% of players to about 3%. So it's just still in the low billions of dollars of new process, substantially north of $100 million a year. But what's exciting is that a year ago, we had about 20 customers using this capability. We could have 30 customers using this capability. So almost half of -- so that is an example of a solution enabled by the network, enabled by the data, artificial intelligence that now has the capability to actually give you a line [indiscernible]. And then there are solutions like diagnostics where every car now, after an auto claim, needs a diagnostic. 5 or 10 years ago, maybe 3% of cars need the scan. About -- every car in the last 2 years have the scan before and after. That creates a complexity that dataset that you can manage that newer solutions [indiscernible] we've just released. And so there's a number of new solutions for it.

Where does the customer success fit into the CCC story as well, too? Because I know Net Promoter Score is a big metric you guys focus on, but it should also incentivize willingness for these customers to track some of these newer solutions.

Yes. Because at the heart of every product we've ever built and delivered is a very fundamental part of our history, whether you're going to be the parts provider, an insurance [indiscernible], we deliver a bottom line ROI that is tangible, that's better. And on every solution we deliver also reduces [indiscernible] almost across the room. And the third thing is when you look at our policy owners, are we impacting them, are we making their processes, are we making everybody's lives are getting much [indiscernible] so you're comparing your plain experience to what maybe you're backbone to what Amazon or what Netflix, and that's really what we're helping our customers [ deliver ].

That makes a ton of sense. Maybe, Brian, from a financial perspective and how you kind of contract, right, what does the typical customer look like for you guys? Kind of how much of the revenue is recurring? What's the right way of thinking about financial metrics there?

Yes. So the vast majority of our revenue is subscription-based. About 80% is subscription-based, 20% is transactional. But even the transactional are part of long-term contracts, and so that is the main revenue, the transactional part as well. Most of our deals are 3- to 5-year deals. So we have really good -- great ability around the revenue model. The cross-sell/upsell story that we're really focused on, kind of the adoption of new solutions is really the build of the revenue going forward. But it's a durable revenue model. It's predictable. And it is a -- in terms of the cross-sell/upsell, it also helps drop through margin as you scale the business.

Right. Okay. Githesh, going back to you here. Thinking about, obviously, bringing value to this overall ecosystem, we talked about subrogation and some of these newer initiatives as well. What does that unlock or some of the challenges carriers are facing, whether it's fraud detection, obviously, providing context around what actually happened and the physical damage or the accident in and of itself?

There's actually quite a number of things that we are now -- we can get data from the vehicles themselves that are kind of important. We can take -- when we take photos, when this customer send us photos of the accident, we can actually compute the physical -- the injury potential from that. We actually do very sophisticated physics around the impact forces of the accident and the likelihood of body injury from that. So we have those capabilities. So there's -- so the innovation that we're doing on a very clean tech stack allows us to really do a range of innovations that all of the different pieces connect to you. Because if you think about a single claim, single claim I'll start with how do I handle the first -- the reporting of the [ accident ]. And then every [indiscernible] of scheduled repair, the payments, subrogation, so we link all of these solutions in a way that delivers a very unique value to our customers.

Where does this transition, if you want to call it that, to the IX Cloud help unlock and enable connectivity of that?

Yes. So we just, as you know, announced the IX Cloud at our conference a few weeks ago. So IX Cloud sits on top of our cloud-based infrastructure. So we've been on the web for about 20 years. Our repair facility customers, we could move them over to the Internet, to the web platform about 20 years ago. So IX Cloud is an event-driven architecture that sits across the [indiscernible] industry and can -- and enables information instantaneously a decision about whether the car should be totaled, whether -- and what parts are ordered, the implications and makes the data available to all the different places and also, we believe, enables the speed at which we can innovate for our customers and solve many, many, many more problems by linking all of these different sets, but in a very, very quick streamline. So think of it as in amplifier of our capabilities.

Sure, sure.

We're not going to charge through the IX Cloud platform. So it really is a platform that clients can roll out. Then our applications, we believe is, as said, an amplifier will drive adoption of the applications. So that's what we're really excited about.

So supporting [indiscernible].

And that's where the customer success really comes from the fact that we can now link all of these things together.

Right, right. So Brian, you've touched on kind of where the historical operating model has been and where we can go with some of these new solutions that are introduced as well. So what's the right way of thinking about kind of the long-term financial profile and how all these components compared?

Yes. So we -- our long-term target that we've put out there is 7% to 10%. That is an organic revenue number. We've broken it down, as the shift goes from where we've been to the -- from the 30% new logos, 80 -- 30% new logos, 70% cross-sell/upsell, it will transition over time where 20% will be coming from new logos, and 80% would be cross-sell/upsell. And then what we're seeing is within the cross-sell/upsell, half would be the emerging solutions that have more recently come to market. And then half of the growth will come from established solutions that have been in the market for a period of time. So that's on the revenue side. On the margin side as well as the overall profile, we're expecting about 100 basis points of margin improvement per year. So we ended last year at 41% margin. We're targeting mid-40s in the guide. There isn't any ceiling on that market. We're just putting a guide in the market that sets up a target that we feel comfortable we can deliver in a reasonable period of time. And then the third is gross profit margins moving towards 80% as well. So those are some of the metrics that we put out as part of the modeling value.

You've done a phenomenal job executing against those over the past several years as well. Maybe you can tap -- test where does casualty -- or excuse me, not casualty, the medical care side of things within -- working on this as well. We haven't really touched on it. And what does that mean from an opportunity perspective, Brian?

Sure. So first and foremost, 1 out of every 5 auto claims has casualty involved. And traditionally, historically, for many, many years, we focus primarily on physical damage, building up the network, skinning that out across the customer base. Over the last several years, we've started to put a little more emphasis on the casualty side of the operation and, frankly, linking those solutions together. So if you look at the dollar claims for the industry, the industry pays out in aggregate dollars about the same for part of physical damage -- repair or the losses [indiscernible]. So from a scale standpoint, the same number of customers we have also used in casualty solution, they should be very comparable throughout this dynamic process. So it's a great opportunity. We expect significantly on leaving out the platform, put a lot of innovation in it, impact dynamics, as example of that, where we've taken part the physics of the act that converted that into the implications of a medical claim from a photo using physics [indiscernible]. So there are many different implications. So we're quite excited about what we can do for our customers and growth.

Again, in terms of financial profile, casualty today is about 10% of revenue. It is growing faster than the total company. So it contributed about 1 point of growth last year. As we continue to see it scale, if you think about it, it converts and becomes as mature as our auto physical damage. It could be a $300 million pipeline for us. So it's really around further client adoption and cross-selling to our sell base and also bringing out these new solutions, which we believe are differentiated. And so we feel really good on the momentum and the progress we're seeing today.

And maybe for both of you as well. So Brian, I think you mentioned $5 billion of the TAM has gone pretty addressable. Why is there -- there's a lot more room to deliver value and innovation across the ecosystem. It's maybe picked up the last few years, but what's the right way of thinking about the future? And maybe customers that are coming to you with challenges, how that kind of fuels your product development?

Yes. So when we look at the $10 billion, as we said, we buy and address [ these ] solutions that we have in the market or will be out. We also look at the $5 billion that is really driving how we can help clients be more efficient, how we can help clients with accuracy and taking [ leakage ] out of the claim and also how we continue to scale the business across the broader ecosystem. So our road map really will inform product solutions that come out, and that incremental $5 billion. But we feel we have -- you want to talk about the advisory council, how we got the feedback.

Yes. So a lot of what we see is, really, if you look at the banking industry, first, the amount of dollars spent in upgraded technology in banking, the insurance industry has typically not spent that level [indiscernible]. So all our customers are now seeing, especially as inflation over the last several years, a real deep desire to upgrade technology. Many, many components of claims processes [indiscernible]. So by digitizing much, much more of the capability, there's a tremendous opportunity. And if you break down that customer comment, we bring our customers in, we have very intimate working relationships with customers. So the very highlighted that we're working with the customer who sold every product and every solution, so the feedback loops are very tight. Our release cycles are tight. We've delivered over a 1,000 releases of software last year and the velocity in which we can deliver results.

Maybe a question we get fairly often, [indiscernible] more. But what's the right way of thinking about autonomous person driving in the ecosystem base? Is that an opportunity for you? Is that a complexity? Is that right around where claims mitigation comes into play? How do we think about that?

Yes. And to your point, people used to ask us that question more often because the -- what we have seen in the -- medium term, think about the next 10 to 15 years, is the complexity of the vehicles because of more cameras, lane departure warning systems, calibration, diagnostics. That's increased a massive amount of complexity that we are helping to solve. And meanwhile, what we've seen over the last 30, 40 years, the claim frequency across the industry has been relatively flat. So we think that the complexity factor will continue to increase, and you're going to need your solutions like ours to be able to solve these complexities. We really are the largest processor of electronic EVs, hybrids for our customers, so we see all the different data sets and -- but the claim frequency, we've not seen any significant change.

Yes. And maybe as a component of that, too, that the age of vehicles on the road continues to get older, obviously, you have a refresh cycle...

Exactly. Refresh cycle is exactly like you said. The refresh cycle as well. A few years ago, the average age in the industry was about 11.5 years. That then increased to 12. It's now creeping up to 12.5, 12.6. And the cost of cars, so there's another full churn of how many years do they actually get [indiscernible].

Right, right. Okay. That's really helpful. Brian, maybe if we go back to kind of the cash generation, profitability profile that we touched on. Very, very high quality. How should we think about sources and uses of capital within that as well, too? Where does expansion into other P&C lines come into play? Obviously, the U.S. business today and, I think, international, where does M&A fit in the equation?

Yes. So we have a very efficient balance sheet. We're 2x levered with net debt. We think about seeing where the capital work, M&A is a focus area. We think about M&A across product expansion. So subrogation, as Githesh mentioned, is the solution we're really excited about in the market. We acquired a business that is the platform for our subrogation solution. That was a small business, but it was a product extension that we see -- or look at from a cross-sell opportunities on our installed base. I think when we look at other adjacency in the P&C, M&A will play a part in that. We also think for an international play, M&A would be a part also. So we do expect M&A to be a larger player and going forward than it has historically. And certainly, our balance sheet give us that flexibility that will help fund us.

Sure. And obviously, it's not [indiscernible].

Exactly. What we said for 7 to 10 guide, that's an organic position. And so M&A would be [indiscernible] with that decision.

Okay. We've covered a lot today, gentlemen. And obviously, there's a lot to get excited about. But maybe as a parting word before we go to the breakout, Githesh, Brian, what excites you most about the next decade of opportunity for CCC?

Yes. I would say the single biggest piece of excitement for us is we work for decades to really build out the customer base, the network capabilities, the datasets we have. And with the release of AI investments we made, the opportunities we see across the board are substantial. So the innovation potential is substantial. So it's a more exciting time that anyone can think of. And also, the customers are excited about adopting faster than we have seen.

I would just add the innovation funnel has never been larger. The new solutions that we've recently brought into the market, the pipeline of new incremental solutions that will be coming into the market this year, it's really robust. And so we're really excited about the adoption of these solutions and the future innovation that's out there.

[indiscernible] that was the last one, but you sparked another question, Githesh, too. Obviously, AI and, obviously, what you guys are investing in is coming top of mind. How is that [ supposed to change ]? Can you shed a light on leveraging data in the [indiscernible]?

In fact, because we are in existing workflows already, we've been able to introduce the AI inside those workflows. So it's actually amplifying the power and the capability of their own people. So our customers might have a small repair facility, a customer might have few employees, our largest repair facility customer has 35,000 employees. Carriers might have 200 employees to tens of thousands. And so what we've seen is in those existing workflows, the introduction of AI that has taken the cognitive load of looking at 200 pages of documents [indiscernible] to be able to do that in seconds, to be able to take a photo, this is exactly what we should do. So all of those things are allowing our customers that [indiscernible] we hold the hands of their policies. So that is truly [indiscernible].

Awesome. I think that's a great place to wrap. Thank you both for joining us today [indiscernible].